Iterative phase-locked limit cycle flux linkage observer, control method, device and system

Abstract

The invention discloses an iterative phase-locked limit cycle flux observer, a control method, a control device and a control system, and the control method comprises the following steps: collecting alpha-beta axis voltage and current signals of a motor, constructing an IPMSM mathematical model under an alpha-beta axis, and calculating to obtain a counter electromotive force vector of the motor; taking the motor back electromotive force vector as input, acquiring motor rotor flux linkage information through an iterative phase-locked limit loop flux linkage observer, and estimating a motor rotating speed and a position signal according to the motor rotor flux linkage information; and the rotating speed and the position signal of the motor are input into a motor closed-loop control system, so that position-sensorless closed-loop control of the permanent magnet synchronous motor is realized. According to the method provided by the invention, the problem of integral drift or phase lag of a traditional flux linkage observer can be avoided, the influence of direct current bias on flux linkage and position observation precision is effectively suppressed, the dynamic response capability of position sensorless control is remarkably improved, and a position estimation error generated in a dynamic process is suppressed.

Description

Technical Field

[0001] The present invention belongs to the field of permanent magnet synchronous motor control, and in particular relates to an iterative phase-locked limit loop flux observer, a control method and device, and a system. Background Art

[0002] Permanent magnet synchronous motor sensorless drive systems achieve high-efficiency, low-maintenance, and high-power density electromechanical energy conversion at low cost. They are widely used in wind turbines, compressors, and rail transit. Based on their principles, they can be categorized as either high-frequency signal injection or fundamental frequency modeling. The high-frequency signal injection method requires injecting an auxiliary signal into the motor stator, which increases system losses and reduces voltage utilization. It is typically used for zero-speed and low-speed operation in permanent magnet synchronous motor sensorless drive systems.

[0003] The fundamental frequency model method requires no additional auxiliary signal injection. Simply by designing an advanced observer based on the motor's fundamental frequency model to estimate back EMF or flux information, accurate speed and position information can be obtained. Many researchers have designed back EMF observers using methods such as model reference adaptation, extended Kalman filters, and sliding mode observers. However, the back EMF amplitude is proportional to the motor speed. When the motor is running at low speeds, non-ideal factors such as inverter nonlinearities, DC bias, and harmonic components can significantly reduce the signal-to-noise ratio of the back EMF component, thereby reducing the control accuracy of the back EMF fundamental frequency model method.

[0004] The fundamental frequency model method based on rotor flux integrates or performs an equivalent integration of the motor's back EMF to obtain rotor flux information, thereby extracting motor speed and position. When using pure integration as the rotor flux observer, integration drift and initial value errors can cause a slope bias in the estimated flux information, resulting in reduced computational accuracy and even divergence. To suppress DC bias, a high-pass filter is often cascaded after the pure integration to address the integration drift problem. This effectively translates to using a low-pass filter as the flux observer. However, this filter causes phase lag and amplitude attenuation in the estimated flux information. The resonant frequency of a second-order generalized integral (with unity gain and zero phase lag) can deviate from 0 Hz. Using a second-order generalized integral as the flux observer avoids the amplitude attenuation and phase lag introduced by the low-pass filter. However, it uses a linear oscillator as the orthogonal signal generator, making the observation performance dependent on the initial value of the integral. Further use of a nonlinear oscillator can improve the robustness of the observer.

[0005] After obtaining the rotor flux signal, a phase-locked loop is usually used to extract the motor speed and position information. However, the traditional phase-locked loop uses a PI controller as a loop filter. Its linear characteristics and fixed parameters cannot meet the frequently changing working conditions of the motor. For example, it cannot achieve accurate tracking when the input is a frequency ramp signal, which limits the use of traditional phase-locked loops in applications where the motor frequency changes rapidly. A new type of iterative phase-locked loop has been proposed in the prior art. It uses the principle of iterative operation to solve equations to search for the motor rotor position to improve the dynamic response capability of the phase-locked loop, and there is no need to adjust the control parameters. However, this method requires 64 iterations to find the best solution to obtain a theoretical observation accuracy of 0.003rad, which will undoubtedly significantly increase the burden on the digital controller.

[0006] In summary, how to achieve high-precision and low-computational burden position sensorless control of permanent magnet synchronous motors has important research significance. Summary of the Invention

[0007] The object of the present invention is to provide an iterative phase-locked limit cycle flux observer, a control method and device, and a system for solving the above-mentioned problems.

[0008] The present invention provides the following technical solutions:

[0009] In a first aspect, the present invention provides a limit cycle flux observer. The limit cycle flux observer is based on a limit cycle oscillator to design a rotor flux observer. The limit cycle flux observer includes:

[0010] The convergence radius setting module is used to set the convergence radius to meet the following requirements: Where A is the convergence radius of the limit cycle system, e sα With e sβ is the back electromotive force signal of the αβ axis motor;

[0011] An observer construction module is used to construct a limit cycle flux observer by introducing a tracking error term of back electromotive force to obtain rotor flux information;

[0012] The limit cycle flux observer is:

[0013]

[0014] Wherein, the superscript “^” represents the estimated quantity, k and γ (k, γ>0) are the adjustable gains of the limit cycle flux observer, and ε e =[ε eα ε eβ ] T is the back-EMF tracking error vector, is the rotor flux vector obtained by the limit cycle flux observer, is the estimated back-EMF DC vector, is the estimated back EMF vector, for The orthogonal vector of

[0015] Estimated back EMF vector and the actual back electromotive force vector e s The transfer function between is expressed as:

[0016]

[0017] The rotor flux vector estimated by the limit cycle flux observer and the actual back electromotive force vector e s The transfer function between is expressed as:

[0018]

[0019] Where Q(s) is and The transfer function between .

[0020] In a second aspect, the present invention provides an iterative phase-locked loop, wherein the iterative phase-locked loop is based on Newton iteration and comprises:

[0021] Normalization module, used to normalize the rotor flux information and calculate the normalized rotor flux in the γδ axis coordinate system;

[0022] The compensation angle setting module is used to divide the entire calculation domain into four regions I-IV according to the sign of the rotor flux in the γδ coordinate system, and set the iterative initial value compensation angle according to the partition;

[0023] The iterative initial value compensation angle θ is set according to the partition c for:

[0024]

[0025] An iterative initial value module is used to compensate areas I and IV to areas II and III according to the initial value compensation angle to determine the iterative initial value;

[0026] The initial value of the iteration θ e(0) Expressed as:

[0027]

[0028] The cost function module is used to obtain the equivalent position error based on the normalized rotor flux in the γδ axis coordinate system and construct a cost function to extract the rotor position;

[0029] The calculation accuracy module is used to calculate the calculation accuracy under different iteration numbers, so as to determine whether the number of iterations is reasonable;

[0030] The differential module is used to obtain the motor speed by differentiating the rotor position after obtaining the rotor position.

[0031] In one embodiment, the equivalent position error is:

[0032]

[0033] Among them, E err is the equivalent position error, is the normalized αβ-axis rotor flux information, is the normalized γδ-axis rotor flux information, is the estimated rotor position error, θ e is the actual value of the rotor position, is the rotor position observation value;

[0034] The rotor position is obtained by constructing a cost function through the equivalent position error;

[0035] The cost function J new for:

[0036]

[0037] The acquisition of the rotor position can be equivalent to solving:

[0038]

[0039] To solve the above equation, define the Newton iteration formula related to the estimated rotor position:

[0040]

[0041] In one embodiment, the difference between the initial iteration value and the motor rotor position is limited to the interval [-π / 2, π / 2] rad, thereby improving the convergence speed of the Newton iteration method and reducing the calculation domain of the Newton iteration method.

[0042] In one embodiment, the calculation accuracy at different iteration numbers is calculated by the following formula:

[0043]

[0044] Among them, θ err(j-1) and θ err(j) is the calculation error between the j-1th and jth iterations, and is the rotor position information calculated at the j-1th and jth iterations.

[0045] In a third aspect, the present invention provides an iterative phase-locked limit cycle flux observer, which is used to obtain motor rotor flux information and extract motor speed and position signals; the extracted motor speed and position signals are used to input into the motor closed-loop control system to realize position sensorless closed-loop control of the permanent magnet synchronous motor; the iterative phase-locked limit cycle flux observer includes the above-mentioned iterative phase-locked loop and the above-mentioned limit cycle flux observer; the limit cycle flux observer is used to obtain motor rotor flux information; the iterative phase-locked loop is used to extract motor speed and position information based on the rotor flux information of the limit cycle flux observer, and feed the speed back to the limit cycle flux observer.

[0046] In a fourth aspect, the present invention provides a permanent magnet synchronous motor control method based on an iterative phase-locked limit cycle flux observer, the method comprising:

[0047] Collect the voltage and current signals of the motor's αβ axes, build the IPMSM mathematical model under the αβ axis system, and calculate the motor's back electromotive force vector;

[0048] The motor back electromotive force vector is used as input, and the motor rotor flux information is obtained through the above-mentioned iterative phase-locked limit cycle flux observer, and the motor speed and position signals are estimated based on the motor rotor flux information;

[0049] The motor speed and position signals are input into the motor closed-loop control system to achieve position sensorless closed-loop control of the permanent magnet synchronous motor.

[0050] In a possible implementation, after obtaining the motor speed, the method further includes: using a low-pass filter to smooth the estimated speed to suppress high-frequency noise introduced by differentiation.

[0051] In a fifth aspect, the present invention provides a permanent magnet synchronous motor control device based on an iterative phase-locked limit cycle flux observer, the device comprising:

[0052] The IPMSM mathematical model module is used to collect the voltage and current signals of the motor's αβ axes, build the IPMSM mathematical model under the αβ axis system, and calculate the motor's back electromotive force vector;

[0053] The above-mentioned iterative phase-locked limit cycle flux observer is used to take the motor back electromotive force vector as input, obtain the motor rotor flux information, and estimate the motor speed and position signals based on the motor rotor flux information;

[0054] The motor speed and position signal transmission module is used to input the motor speed and position signals extracted by the iterative phase-locked limit loop flux observer into the motor closed-loop control system, realizing position sensorless closed-loop control of the permanent magnet synchronous motor.

[0055] In a sixth aspect, the present invention provides a permanent magnet synchronous motor control system, the system comprising: the above-mentioned permanent magnet synchronous motor control device based on iterative phase-locked limit cycle flux observer.

[0056] Beneficial effects of the present invention:

[0057] (1) The present invention designs a rotor flux observer based on a nonlinear limit cycle oscillator. By designing a unique closed trajectory of the back-electromotive force limit cycle system, accurate observation of the motor rotor flux information is achieved, thereby solving the problems of integral drift or phase lag in traditional flux observers and suppressing the influence of DC bias on the accuracy of flux and position observation. It can be used in asynchronous motor position sensorless control technology and synchronous reluctance motor position sensorless control technology.

[0058] (2) The present invention designs a new iterative phase-locked loop, which sets the iterative initial value compensation angle by partitioning the rotor flux signal, and realizes high-precision rotor position observation through three iterative operations based on Newton iteration operation. It can avoid the adjustment of phase-locked loop parameters and improve the dynamic response capability of position sensorless control. It can be used for grid-connected synchronization technology, asynchronous motor position sensorless control technology and synchronous reluctance motor position sensorless control technology.

[0059] (3) The present invention combines a limit cycle flux observer with an iterative phase-locked loop to form an iterative phase-locked limit cycle flux observer, which is used to improve the dynamic response capability of the position sensorless control of the permanent magnet synchronous motor and realize the position sensorless control of the permanent magnet synchronous motor with high precision and low computational burden. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings, as part of this disclosure, are intended to provide a further understanding of the disclosure. The exemplary embodiments of the disclosure and their descriptions are intended to explain the disclosure and do not constitute undue limitations thereon. Obviously, the drawings described below are merely examples, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0061] Figure 1 The partitioning of the entire calculation domain and the setting of the compensation angle provided in one embodiment of the present invention;

[0062] Figure 2 A control block diagram of an iterative phase-locked limit cycle flux observer provided in one embodiment of the present invention;

[0063] Figure 3 This is a flow chart of a permanent magnet synchronous motor control method provided in one embodiment of the present invention;

[0064] Figure 4 Bode diagram of a pure integrator, a low-pass filter, and a limit cycle flux observer provided in one embodiment of the present invention;

[0065] Figure 5 is a Bode diagram of a limit cycle flux observer under parameter conditions provided in one embodiment of the present invention; Figure 5 (a) Bode diagram of the limit cycle flux observer under different k conditions; Figure 5 (b) Bode diagram of the limit cycle flux observer under different γ conditions;

[0066] Figure 6 E under different position error conditions provided in one embodiment of the present invention err With J new ;

[0067] Figure 7 A schematic structural diagram of a permanent magnet synchronous motor control system provided in one embodiment of the present invention;

[0068] Figure 8 The steady-state experimental comparison results of the pure integral, low-pass filter and limit cycle flux observer provided in one embodiment of the present invention are shown in FIG. Figure 8 (a) is the steady-state experimental result of pure integration, Figure 8 (b) is the steady-state experimental result of the low-pass filter. Figure 8 (c) is the steady-state experimental result of the limit cycle flux observer;

[0069] Figure 9 The comparative results of the rotor flux experiment under 10V DC disturbance of α-axis back electromotive force provided in one embodiment of the present invention are shown in FIG. Figure 9 (a) is the rotor flux experimental result of the low-pass filter, Figure 9 (b) is the steady-state experimental result of the limit cycle flux observer;

[0070] Figure 10 An embodiment of the present invention provides experimental comparison results of a traditional phase-locked loop and an iterative phase-locked loop in rapid acceleration and deceleration; wherein, Figure 10 (a) is the experimental result of the traditional phase-locked loop. Figure 10 (b) is the experimental result of iterative phase-locked loop;

[0071] It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but rather to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The following embodiments are used to illustrate the present invention but are not used to limit the scope of the present invention.

[0073] The present invention aims to solve the problems of integral drift or phase lag in the traditional flux observer in the existing permanent magnet synchronous motor position sensorless control technology and the problem that the traditional phase-locked loop cannot meet the frequent changes in the motor's working conditions, so that the permanent magnet synchronous motor position sensorless drive system can operate efficiently and stably.

[0074] Example 1

[0075] The disclosed embodiment of the present invention provides a limit cycle flux observer. The limit cycle flux observer is based on a limit cycle oscillator to design a rotor flux observer. The limit cycle flux observer includes:

[0076] The convergence radius setting module is used to set the convergence radius to meet the following requirements: Where A is the convergence radius of the limit cycle system, e sα With e sβ is the back electromotive force of the αβ shaft motor;

[0077] An observer construction module is used to construct a limit cycle flux observer by introducing a tracking error term of back electromotive force to obtain rotor flux information;

[0078]

[0079] Wherein, the superscript “^” represents the estimated quantity, k and γ (k, γ>0) are the adjustable gains of the limit cycle flux observer, and ε e＝ [ε eα ε eβ ] T is the back-EMF tracking error vector, is the rotor flux vector obtained by the limit cycle flux observer, is the estimated back-EMF DC vector, is the estimated back EMF vector, for The orthogonal vector of .

[0080] When the system is in steady state, the system trajectory converges to a closed orbit, which is the nonlinear part of the limit cycle flux observer. Then for the Laplace operator and The transfer function between is expressed as:

[0081]

[0082] From this formula, we can see that when the system is in steady state, Q(s) can be used as an integrator, and the numerator It can ensure the normalization of the observed magnetic flux signal.

[0083] Furthermore, the limit cycle flux observer is converted to the s domain, and we have:

[0084]

[0085] use Delocalize the above formula:

[0086]

[0087] Furthermore, the estimated back EMF vector and the actual back electromotive force vector e s The transfer function between is expressed as:

[0088]

[0089] Furthermore, the rotor flux vector estimated by the limit cycle flux observer and the actual back electromotive force vector e s The transfer function between is expressed as:

[0090]

[0091] Where Q(s) is and The transfer function between .

[0092] Taking the DC bias E0 / s as the input of the limit cycle flux observer, we can obtain the following from the Laplace final value theorem:

[0093]

[0094] Example 2

[0095] The Newton iteration method is an iterative method for solving nonlinear equations with an extremely fast convergence speed. The convergence speed is related to the selection of the initial value of the iteration. The closer the initial value of the iteration is to the optimal result, the faster the convergence speed.

[0096] Based on Newton iteration, an iterative phase-locked loop is provided in the disclosed embodiment of the present invention. The iterative phase-locked loop includes:

[0097] Normalization module, used to normalize the rotor flux information and calculate the normalized rotor flux in the γδ axis coordinate system;

[0098] The compensation angle setting module is used to divide the entire calculation domain into four regions I-IV according to the sign of the rotor flux in the γδ coordinate system, and set the iterative initial value compensation angle according to the partition;

[0099] An iterative initial value module is used to compensate areas I and IV to areas II and III according to the initial value compensation angle to determine the iterative initial value;

[0100] The cost function module is used to obtain the equivalent position error based on the normalized rotor flux in the γδ axis coordinate system and construct a cost function to extract the rotor position;

[0101] The calculation accuracy module is used to calculate the calculation accuracy under different iteration numbers, so as to determine whether the number of iterations is reasonable;

[0102] The differential module is used to obtain the motor speed by differentiating the rotor position after obtaining the rotor position.

[0103] In order to facilitate the design of the iterative phase-locked loop, the rotor flux signal obtained by the limit cycle flux observer is normalized:

[0104]

[0105] in, is the normalized rotor flux vector. In order to select the initial value of the iteration close to the optimal result, the normalized rotor flux in the γδ axis (i.e., the estimated dq axis) coordinate system is calculated:

[0106]

[0107] in, and is the normalized γδ-axis rotor flux, is the estimated rotor position error.

[0108] Generally, the position observation value of the previous period is used As the initial value of iteration, in order to facilitate the initial value of iteration to approach the optimal result, the partition of the entire computational domain is as follows Figure 1 As shown in the figure, the entire calculation domain is divided into four regions (I-IV) according to the sign of the rotor flux in the γδ coordinate system, and the iterative initial value compensation angle θ is set according to the partition. c :

[0109]

[0110] The initial compensation angle can compensate areas I and IV to areas II and III, so the final iterative initial value θ e(0) Expressed as:

[0111]

[0112] Iteration initial value θ e(0) The difference θ from the motor rotor position err It can be limited to the interval (-π / 2,π / 2) rad, thereby improving the convergence speed of the Newton iteration method and reducing the calculation domain of the Newton iteration method.

[0113] Furthermore, the equivalent position error of the rotor flux in the normalized γδ axis coordinate system is designed:

[0114]

[0115] Among them, E err is the equivalent position error, is the normalized αβ-axis rotor flux information, is the normalized γδ-axis rotor flux information, is the estimated rotor position error, θ e is the actual value of the rotor position, is the rotor position observation value;

[0116] The rotor position is obtained by constructing a cost function through the equivalent position error;

[0117] The cost function J new for:

[0118]

[0119] The acquisition of the rotor position can be equivalent to solving:

[0120]

[0121] To solve the above equation, define the Newton iteration formula related to the estimated rotor position:

[0122]

[0123] Furthermore, for iterative phase-locked loops, the number of iterations is proportional to the computational effort of the digital controller. To design a reasonable number of iterations, it is necessary to determine the computational accuracy of the Newton iteration method at different numbers of iterations. The computational accuracy at different numbers of iterations can be calculated using the following formula:

[0124]

[0125] Among them, θ err(j-1) and θ err(j) is the calculation error between the j-1th and jth iterations, and is the rotor position information calculated at the j-1th and jth iterations.

[0126] After obtaining the rotor position, the motor speed can be obtained by differentiating the rotor position.

[0127] Example 3

[0128] The disclosed embodiment of the present invention provides an iterative phase-locked limit cycle flux observer, which is used to extract motor speed and position signals by obtaining motor rotor flux information; the extracted motor speed and position signals are used to input into the motor closed-loop control system to realize position sensorless closed-loop control of the permanent magnet synchronous motor; the iterative phase-locked limit cycle flux observer includes the above-mentioned iterative phase-locked loop and the above-mentioned limit cycle flux observer; the limit cycle flux observer is used to obtain motor rotor flux information; the iterative phase-locked loop is used to extract motor speed and position information based on the rotor flux information of the limit cycle flux observer, and feed the speed back to the limit cycle flux observer.

[0129] The control block diagram of the iterative phase-locked limit cycle flux observer is shown in Figure 2. Figure 2 For the description of the limit cycle flux observer and the iterative phase-locked loop, please refer to the description of the same or similar parts above, which will not be repeated here.

[0130] Example 4

[0131] Reference Figure 3 As shown, the present disclosure provides a permanent magnet synchronous motor control method based on an iterative phase-locked limit cycle flux observer, which specifically includes the following steps:

[0132] Step S100: collecting the voltage and current signals of the motor αβ axes, constructing an IPMSM mathematical model under the αβ axis system, and calculating the motor back electromotive force vector.

[0133] Furthermore, the mathematical model of IPMSM under the αβ axis system can be expressed as:

[0134]

[0135] where u α 、u β is the stator voltage αβ axis component, i α 、i β is the stator current αβ axis component, R s With L q is the stator resistance and q-axis inductance, p is the differential operator, θ e is the motor rotor position, ψ af is the effective magnetic flux, ψ af It can be expressed as:

[0136] ψ af =ψ f +(L d -L q )i d

[0137] Among them L dis the d-axis inductance. The vector form of the IPMSM mathematical model in the αβ axis system is:

[0138] u s =R s i s +pψ s

[0139] Among them, u s =[u α u β ] T ,i s =[i α i β ] T , ψ s is the stator flux vector, ψ s It can be expressed as:

[0140] ψ s =L q i s +ψ af [cosθ e sinθ e )] T

[0141] Furthermore, the motor rotor flux vector is obtained based on the IPMSM mathematical model under the αβ axis system.

[0142] According to the above formula, the rotor flux vector can be obtained:

[0143] ψ r =∫(u s -R s i s -pL q i s )dt=∫e s dt

[0144] Among them, ψ r =[ψ rα ψ rβ ] T =[ψ af cosθ e ψ af sinθ e ] T is the rotor flux vector, e s =[e sα e sβ ] T is the back electromotive force vector.

[0145] Step S200: taking the motor back electromotive force vector as input, obtaining the motor rotor flux information through an iterative phase-locked limit cycle flux observer, and estimating the motor speed and position signals based on the motor rotor flux information.

[0146] For the description of the iterative phase-locked limit cycle flux observer, please refer to the description of the same or similar parts above, which will not be repeated here.

[0147] For general linear sinusoidal oscillators (such as second-order generalized integrators), the system has a series of closed orbits, and external disturbances or parameter mismatches may cause the system orbit to shift. However, for nonlinear limit cycle oscillators, the system has only a single closed trajectory. This characteristic makes the limit cycle oscillator robust to external interference near the convergence radius A, thereby ensuring the stability of the system. In addition, the limit cycle oscillator does not depend on the initial conditions of the system. Benefiting from the above advantages, the present invention designs a rotor flux observer based on the limit cycle oscillator to solve the problems of integral drift or phase lag in traditional flux observation schemes, and suppress the influence of DC bias on the accuracy of flux and position observation.

[0148] To verify the ability of the limit cycle flux observer to suppress DC bias and high-order harmonics, the Bode diagrams of pure integrator, low-pass filter and limit cycle flux observer are shown in Figure 2. Figure 4 As shown in the figure, the motor operating frequency is 100 Hz, the LPF cutoff frequency is 100 rad / s, and the limit cycle flux observer parameters are k = 1.414 and γ = 85. A pure integrator produces a time-varying ramp bias, causing saturation of the estimated flux. The low-pass filter can suppress DC components and higher-order harmonics with an amplitude decay rate of -20 dB / decade, but this can cause significant amplitude decay and phase shift. The limit cycle flux observer also has the ability to suppress DC components and higher-order harmonics, with amplitude decay rates of -20 dB / decade below and -40 dB / decade above the center frequency, respectively.

[0149] Figure 5 The Bode diagram of the limit cycle flux observer under different k and γ conditions is shown. Figure 5 As shown in (a), increasing the parameter k is conducive to improving the observer bandwidth, thereby improving the dynamic response capability of the system, but it will reduce the frequency selectivity of the observer. Therefore, the selection of parameter k requires a balance between the dynamic response capability and frequency selectivity of the observer. Figure 5 As shown in (b), increasing the parameter γ is beneficial to improving the DC bias suppression capability of the observer, but an excessively large parameter γ will cause the orthogonal signal to oscillate outside the resonant frequency.

[0150] After obtaining the motor rotor flux information, an iterative phase-locked loop based on Newton iteration is used to extract the motor speed and position information.

[0151] According to the calculation accuracy formula, the estimation error of the Newton iteration method under different initial value conditions and different number of iterations is shown in Table 1. It can be seen from the table that even if there is an error of ±π / 2rad in the initial value of the iteration, the estimation error can be limited to 4.73×10 -6 rad, which can meet the accuracy requirements of most fixed-point or floating-point operations.

[0152] Table 1 Estimation error of Newton iteration method after different numbers of iterations under different initial values

[0153]

[0154] Figure 6 The E under different position error conditions is given. err With J new As can be seen from the figure, the cost function J new The entire computational domain contains only one convergence point, that is, only by minimizing the cost function J new , the position estimation error can converge to only 0rad.

[0155] Step S300: Input the motor speed and position signals into the motor closed-loop control system to implement position sensorless closed-loop control of the permanent magnet synchronous motor.

[0156] In a possible implementation, after obtaining the motor speed, the method further includes: using a low-pass filter to smooth the estimated speed to suppress high-frequency noise introduced by differentiation.

[0157]

[0158] Where k represents the sampling time, T s is the sampling period.

[0159] The following is an embodiment of a permanent magnet synchronous motor control device based on an iterative phase-locked limit cycle flux observer according to the present invention, which can be used to implement an embodiment of a permanent magnet synchronous motor control method based on an iterative phase-locked limit cycle flux observer according to the present invention. For details not disclosed in the embodiment of the permanent magnet synchronous motor control device based on an iterative phase-locked limit cycle flux observer according to the present invention, please refer to the embodiment of the permanent magnet synchronous motor control method based on an iterative phase-locked limit cycle flux observer according to the present invention.

[0160] Example 5

[0161] An exemplary embodiment of the present invention provides a permanent magnet synchronous motor control device based on an iterative phase-locked limit cycle flux observer, referring to Figure 7Schematic diagram of the permanent magnet synchronous motor control system structure. The permanent magnet synchronous motor control device can be implemented as all or part of the terminal through software, hardware, or a combination of both. The permanent magnet synchronous motor control device based on iterative phase-locked limit cycle flux observer includes:

[0162] The IPMSM mathematical model module is used to collect the voltage and current signals of the motor's αβ axes, build the IPMSM mathematical model under the αβ axis system, and calculate the motor's back electromotive force vector;

[0163] The above-mentioned iterative phase-locked limit cycle flux observer is used to take the motor back electromotive force vector as input, obtain the motor rotor flux information, and extract the motor speed and position signals based on the motor rotor flux information;

[0164] The motor speed and position signal transmission module is used to input the motor speed and position signals extracted by the iterative phase-locked limit loop flux observer into the motor closed-loop control system, realizing position sensorless closed-loop control of the permanent magnet synchronous motor.

[0165] Optionally, the permanent magnet synchronous motor control device based on the iterative phase-locked limit cycle flux observer further includes a filter module for smoothing the estimated speed using a low-pass filter to suppress high-frequency noise introduced by differentiation.

[0166] It should be noted that the above-mentioned embodiment provides a permanent magnet synchronous motor control device based on an iterative phase-locked limit cycle flux observer, and only uses the division of the above-mentioned functional modules as an example when executing the permanent magnet synchronous motor control method based on an iterative phase-locked limit cycle flux observer. In actual applications, the above-mentioned functions can be distributed to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the above-mentioned embodiment provides a permanent magnet synchronous motor control device based on an iterative phase-locked limit cycle flux observer and the embodiment of the permanent magnet synchronous motor control method based on an iterative phase-locked limit cycle flux observer. The embodiment of the permanent magnet synchronous motor control method based on an iterative phase-locked limit cycle flux observer is based on the same concept. The implementation process is detailed in the embodiment of the permanent magnet synchronous motor control method based on an iterative phase-locked limit cycle flux observer, and will not be repeated here.

[0167] Continue to refer to Figure 7 As shown, in one embodiment, a permanent magnet synchronous motor control system is proposed. The system includes the above-mentioned permanent magnet synchronous motor control device based on iterative phase-locked limit cycle flux observer.

[0168] The specific working process of the system is as follows: the estimated rotor electrical angular velocity is subtracted from the given rotor electrical angular velocity to obtain a speed difference; the speed difference is input into the maximum torque current ratio (MTPA) controller to obtain the dq axis given current; the three-phase current of the permanent magnet synchronous motor is acquired through A / D sampling, and the three-phase current is sequentially subjected to Clark transformation and Park transformation to obtain the current feedback value; the dq axis given current is subtracted from the current feedback value to obtain the current difference; the current difference is input into the PI controller to obtain the dq axis reference voltage; the dq axis reference voltage is subjected to coordinate transformation to obtain the αβ axis voltage; the αβ axis voltage is input into the SVPWM modulation module to output the duty cycle signal; the duty cycle signal is input into the inverter to control the inverter on and off and the above-mentioned permanent magnet synchronous motor control device. Based on the description of the control device, please refer to the description of the same or similar parts above, which will not be repeated here.

[0169] The beneficial effects of the present invention were verified using a 750W permanent magnet synchronous motor experimental platform. The motor parameters are: rated frequency 250Hz, rated speed 3000rpm, pole pair number 5, d-axis inductance 4.7mH, q-axis inductance 6.7mH, stator resistance 0.9Ω, permanent magnet flux linkage 0.054Wb, and rated current 4.2A. A hysteresis brake was used as the motor load, a two-level three-phase inverter was used to drive the permanent magnet synchronous motor, and a TMS320F28335 DSP was used to implement the control algorithm. Both the sampling and switching frequencies were 10kHz.

[0170] Figure 8 The steady-state experimental comparison results of pure integration, low-pass filter and iterative phase-locked limit loop flux observer are shown in Figure 2. The motor speed is 300 rpm. Figure 8 (a) is the steady-state experimental result of pure integration, Figure 8 (b) is the steady-state experimental result of the low-pass filter. Figure 8 (c) is the steady-state experimental result of the iterative phase-locked limit cycle flux observer. Figure 8 As shown in (a), due to the presence of DC disturbance in the back electromotive force, the stator flux signal estimated by pure integration deviates seriously from the ideal flux trajectory, resulting in the inability to track the motor rotor position signal; Figure 8 As shown in (b), since the low-pass filter is equivalent to the cascade of pure integration and high-pass filters, the rotor flux signal estimated by the low-pass filter has significant phase advance and amplitude attenuation; Figure 8 As shown in (c), the motor rotor flux signal estimated by the iterative phase-locked limit cycle flux observer is close to the ideal flux trajectory and can accurately track the motor rotor position signal.

[0171] Figure 9 The comparison results of the rotor flux experiment under 10V DC disturbance of α-axis back electromotive force are shown in Figure 2, where the motor speed is 300rpm. Figure 9(a) is the rotor flux experimental result of the low-pass filter, Figure 9 (b) is the steady-state experimental result of the iterative phase-locked limit cycle flux observer. Figure 9 As shown in (a), after applying a 10V DC disturbance to the α-axis back electromotive force, the α-axis rotor flux signal estimated by the low-pass filter will produce a DC bias, which will lead to a fundamental frequency disturbance of the estimated rotor position; Figure 9 As shown in (b), after a 10V DC disturbance is applied to the α-axis back EMF, the iterative phase-locked limit loop flux observer can effectively compensate for the α-axis flux DC bias and converge to a steady state after two electrical cycles. During the entire operation, the rotor position error is within ±10.0 degrees, indicating that the iterative phase-locked limit loop flux observer has good anti-disturbance performance and observation accuracy.

[0172] Figure 10 The experimental comparison results of the traditional phase-locked loop and the iterative phase-locked loop in rapid acceleration and deceleration are shown in Figure 2. The speed variation trend is 500-1725-3000-2000-1000, and the acceleration in acceleration and deceleration is 1500rpm / s and 800rpm / s respectively. Figure 10 (a), the maximum position estimation error of the traditional phase-locked loop can reach 27.0 degrees during the entire dynamic process. Figure 10 (b) After adopting the iterative phase-locked loop, the maximum position estimation error can be limited to 8.4 degrees during the entire dynamic process, indicating that the iterative phase-locked limit loop flux observer can significantly improve the dynamic response capability of position sensorless control and suppress the position estimation error generated by the dynamic process.

[0173] The above experimental effect diagrams show that the permanent magnet synchronous motor control method of the present invention can avoid the problems of integral drift or phase lag in traditional flux observers, effectively suppress the influence of DC bias on the accuracy of flux and position observation, and significantly improve the dynamic response capability of position sensorless control, thereby suppressing the position estimation error generated by the dynamic process.

[0174] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0175] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A limit cycle flux observer, characterized in that: The limit cycle flux observer designs a rotor flux observer based on a limit cycle oscillator, and the limit cycle flux observer includes: The convergence radius setting module is used to set the convergence radius to meet: Where A is the convergence radius of the limit cycle system, e sα With e sβ is the back electromotive force signal of the αβ axis motor; An observer construction module is used to construct a limit cycle flux observer by introducing a tracking error term of back electromotive force to obtain rotor flux information; The limit cycle flux observer is: Wherein, the superscript "^" represents the estimated quantity, k and γ (k, γ>0) are the adjustable gains of the limit cycle flux observer, and ε e =[ε eα ε eβ ] T is the back-EMF tracking error vector, is the rotor flux vector obtained by the limit cycle flux observer, is the estimated back-EMF DC vector, is the estimated back EMF vector, for Orthogonal vector of ; Estimated back EMF vector The actual back electromotive force vector e s The transfer function between is expressed as: The rotor flux vector estimated by the limit cycle flux observer The actual back electromotive force vector e s The transfer function between is expressed as: Where Q(s) is and The transfer function between .

2. An iterative phase-locked loop, characterized in that: The iterative phase-locked loop is based on Newton iteration, and the iterative phase-locked loop includes: The normalization module is used to normalize the rotor flux information and calculate the normalized rotor flux in the γδ axis coordinate system; The compensation angle setting module is used to divide the entire calculation domain into four regions I-IV according to the sign of the rotor flux in the γδ coordinate system, and set the iterative initial value compensation angle according to the partitions; The iterative initial value compensation angle is set according to the partition as follows: Among them, θ c To set the initial value compensation angle of iteration according to the partition, and is the rotor flux of γδ axis; An iterative initial value module is used to compensate the rotor position estimation error from regions I and IV to regions II and III according to the initial value compensation angle, and determine an iterative initial value; The initial value of the iteration is expressed as: Among them, θ e(0) is the initial value of the iteration, is the position observation value of the previous period; The cost function module is used to obtain the equivalent position error based on the normalized rotor flux in the γδ axis coordinate system and construct a cost function to extract the rotor position; The calculation accuracy module is used to calculate the calculation accuracy under different iteration times, so as to determine whether the iteration times are reasonable; The differential module is used to obtain the motor speed by differentiating the rotor position after obtaining the rotor position.

3. The iterative phase-locked loop according to claim 2, characterized in that: The equivalent position error is: Among them, E err is the equivalent position error, is the normalized αβ-axis rotor flux information, is the normalized γδ-axis rotor flux information, is the estimated rotor position error, θ e is the actual value of the rotor position, is the observed value of the rotor position; The rotor position is obtained by constructing a cost function through the equivalent position error; The cost function J new for: The acquisition of the rotor position can be equivalent to solving: To solve the above equation, define the Newton iteration formula related to the estimated rotor position:

4. The iterative phase-locked loop according to claim 2, characterized in that: The difference between the initial iteration value and the motor rotor position is limited to the interval [-π / 2,π / 2] rad, thereby improving the convergence speed of the Newton iteration method and reducing the calculation domain of the Newton iteration method.

5. The iterative phase-locked loop according to claim 2, characterized in that: The calculation accuracy under different iteration numbers is calculated by the following formula: Among them, θ err(j-1) With θ err(j) is the calculation error between the j-1th and jth iterations, and is the rotor position information calculated at the j-1th and jth iterations.

6. An iterative phase-locked limit cycle flux observer, characterized in that: The iterative phase-locked limit cycle flux observer is used to obtain the motor rotor flux information and extract the motor speed and position signals; the extracted motor speed and position signals are used to input into the motor closed-loop control system to realize position sensorless closed-loop control of the permanent magnet synchronous motor; the iterative phase-locked limit cycle flux observer includes the limit cycle flux observer described in claim 1 and the iterative phase-locked loop described in any one of claims 2 to 5; the limit cycle flux observer is used to obtain the motor rotor flux information; the iterative phase-locked loop is used to extract the motor speed and position information according to the rotor flux information of the limit cycle flux observer, and feed the speed back to the limit cycle flux observer.

7. A permanent magnet synchronous motor control method based on iterative phase-locked limit cycle flux observer, characterized in that: The method comprises: Collect the voltage and current signals of the motor's αβ axis, build the IPMSM mathematical model under the αβ axis system, and calculate the motor's back electromotive force vector; Taking the motor back electromotive force vector as input, obtaining the motor rotor flux information through the iterative phase-locked limit cycle flux observer described in claim 6, and estimating the motor speed and position signal according to the motor rotor flux information; The motor speed and position signals are input into the motor closed-loop control system to realize position sensorless closed-loop control of the permanent magnet synchronous motor.

8. The permanent magnet synchronous motor control method based on iterative phase-locked limit cycle flux observer according to claim 7 is characterized in that: After obtaining the motor speed, the following steps are also included: using a low-pass filter to smooth the estimated speed to suppress the high-frequency noise introduced by the differential.

9. A permanent magnet synchronous motor control device based on iterative phase-locked limit cycle flux observer, characterized in that: The device comprises: IPMSM mathematical model module, used to collect the voltage and current signals of the motor αβ axis, build the IPMSM mathematical model under the αβ axis system, and calculate the motor back electromotive force vector; The iterative phase-locked limit cycle flux observer described in claim 6 is used to take the motor back electromotive force vector as input, obtain the motor rotor flux information, and estimate the motor speed and position signal based on the motor rotor flux information; The motor speed and position signal transmission module is used to input the motor speed and position signals extracted by the iterative phase-locked limit loop flux observer into the motor closed-loop control system to realize position sensorless closed-loop control of the permanent magnet synchronous motor.

10. A permanent magnet synchronous motor control system, characterized in that: The system includes: the permanent magnet synchronous motor control device based on iterative phase-locked limit cycle flux observer as described in claim 9.

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